How to import an excel file into Python using Pandas?
It is not always possible to get the dataset in CSV format. So, Pandas provides us the functions to convert datasets in other formats to the Data frame. An excel file has a ‘.xlsx’ format.
Before we get started, we need to install a few libraries.
pip install pandas pip install xlrd
For importing an Excel file into Python using Pandas we have to use pandas.read_excel() function.
Syntax: pandas.read_excel(io, sheet_name=0, header=0, names=None,….)
Return: DataFrame or dict of DataFrames.
Let’s suppose the Excel file looks like this:
Now, we can dive into the code.
Example 1: Read an Excel file.
Python3
import pandas as pd df = pd.read_excel("sample.xlsx") print(df) |
Output:
Example 2: To select a particular column, we can pass a parameter “index_col“.
Python3
import pandas as pd # Here 0th column will be extracted df = pd.read_excel("sample.xlsx", index_col = 0) print(df) |
Output:
Example 3: In case you don’t prefer the initial heading of the columns, you can change it to indexes using the parameter “header”.
Python3
import pandas as pd df = pd.read_excel('sample.xlsx', header = None) print(df) |
Output:
Example 4: If you want to change the data type of a particular column you can do it using the parameter “dtype“.
Python3
import pandas as pd df = pd.read_excel('sample.xlsx', dtype = {"Products": str, "Price":float}) print(df) |
Output:
Example 5: In case you have unknown values, then you can handle it using the parameter “na_values“. It will convert the mentioned unknown values into “NaN”
Python3
import pandas as pd df = pd.read_excel('sample.xlsx', na_values =['item1', 'item2']) print(df) |
Output:
